Neuromonitoring is a subfield of clinical patient monitoring focused on measuring various aspects of brain function and on changes therein caused by drugs commonly used to induce and maintain anesthesia in an operation room or sedation in patients under critical or intensive care.
Electroencephalography (EEG) is a well-established method for assessing brain activity. When measurement electrodes are attached on the skin of the skull surface, the weak biopotential signals generated in the pyramid cells of the cortex may be recorded and analyzed. The EEG has been in wide use for decades in basic research of the neural systems of the brain as well as in the clinical diagnosis of various central nervous system diseases and disorders.
Electromyography (EMG) is a method for recording electrical biopotentials of muscles. In an EMG measurement, the electrodes are attached onto the surface of the skin overlying a muscle. When a biopotential signal is recorded from the forehead of a subject, the recorded signal indicates both the activity of the facial muscles (fEMG) and the brain (EEG).
One of the special applications of the EEG, which has received attention recently, is the use of a processed EEG signal for objective quantification of the amount and type of brain activity for the purpose of determining the level of consciousness of a patient. In its simplest form, the utilization of an EEG signal allows the automatic detection of the alertness of an individual, i.e. if he or she is awake or asleep. This has become an issue of increased interest, both scientifically and commercially, in the context of measuring the depth of unconsciousness induced by anesthesia during surgery.
Another important component of balanced anesthesia is analgesia which means prevention of pain reactions of a patient by administration of pain medication. Adequate analgesia reduces surgical stress and there is firm evidence that it decreases postoperative morbidity. Awareness during surgery with insufficient analgesia may lead to a post-traumatic stress disorder. Low quality pre- and intra-operative analgesia makes it difficult to select the optimal pain management strategy later on. More specifically, it may cause exposure to unwanted side effects during the recovery from the surgery. If the anesthesia is too light and involves insufficient hypnosis, it may cause traumatic experiences both for the patient and for the anesthesia personnel. From an economical point of view, if the anesthesia is too deep, it may cause increased perioperative costs through extra use of drugs and time, and extend the time required for post-operative care.
Virtually every patient being cared for in an intensive care unit, for example, receives some form of sedation. However, the control of the depth of the sedation administered to a patient is still problematic, and therefore oversedation and undersedation are both common occurrences in intensive care units. At present, monitoring the level of sedation is mainly handled by using subjective observations from the patient. Various sedation assessment scales have been developed for subjectively assessing the level of sedation, the Ramsay Score being one of the most widely used tools for this purpose. Inappropriate sedation can lead to an adverse clinical outcome and reduce treatment efficacy in critical care settings. Oversedation may cause various complications, such as cardiovascular instability, and it may also increase the length of stay in the hospital and prolong the usage time of expensive facilities, such as the intensive care unit. Undersedation, in turn, may result in patient anxiety and agitation, which can further interfere with care, especially with that of neurological patients, and result in harm to the patient and the nursing staff.
The depth of hypnosis is not directly measurable. Therefore, drug delivery systems have to derive the level of hypnosis from a surrogate signal or from indirectly measured parameters. The most common and popular surrogate signal for this purpose is the EEG, from which several parameters may be determined. The basic reason for the insufficiency of a single parameter is the variety of drugs and the complexity of the drug effects on the EEG signal in human brains. However, during the past few years, some commercial validated devices for measuring the level of consciousness and/or awareness in clinical set-up during anesthesia or sedation have become available. Such devices, which are based on a processed EEG signal and examine the signal as a whole with its multiple features, are marketed by GE Healthcare Finland Oy, Kuortaneenkatu 2, FIN-00510 Helsinki (Entropy Index) and by Aspect Medical Systems, Inc., 141 Needham Street, Newton, Mass. 02464, U.S.A. (Bispectral Index, BIS™).
The above devices utilize spectral analysis, which is a traditional technique in EEG signal monitoring. A spectral analysis based on multiple orders of the spectrum is commonly referred to as a higher-order spectral analysis. Power spectrum is a second order spectrum, bispectrum a third order spectrum, and trispectrum a fourth order spectrum, for example. The nomination arises from statistics, where the (k−1)-dimensional Fourier transform of the k-th order cumulant of a given time series produces the k-th order spectrum.
The advantages of a spectral analysis of an order higher than two are, for example, the ability to describe non-Gaussian processes and to preserve phase, immunity to Gaussian noise, and the ability to characterize nonlinearities. Irrespective of the spectral order, a spectral analysis may be performed based on various techniques. While Fourier transform is an efficient method computationally, other methods, like autoregressive modeling, for example, may also be used. Further information about higher-order spectral analysis can be found in Athina P. Petropulu, Higher-Order Spectral Analysis, The Biomedical Engineering Handbook (Edit. Joseph D. Bronzino), Second Edition, Vol. 1, pp. 57.1-57.17, and references therein.
In addition to the EEG signal data, EMG signal data obtained from facial muscles (fEMG) of the forehead is used for monitoring purposes during anesthesia and intensive care. Recovering facial muscle activity is often the first indicator of the patient approaching consciousness. When this muscle activity is sensed by electrodes placed appropriately, it provides an early indication that the patient is emerging from anesthesia. Similarly, these electrodes can sense pain reactions when the anesthesia is not adequate due to inadequate analgesia. So, the EMG signals give an early warning of arousal and may also be indicative of inadequate analgesia.
In connection with anesthesia, the patient is administered hypnotic, analgesic, and neuromuscular blocking agents. However, a certain drug is not normally a pure hypnotic or a pure analgesic, but the drugs normally have additive effects. The anesthetics, i.e. drugs used to produce anesthesia, may also be divided into different groups according to the site of their action. This is discussed briefly in the following.
Glutamate is the most important excitatory transmitter in the central nervous system. Glutamate is involved in sensory processing, motor control and higher cortical functions, including memory and learning. Glutamate acts both through ligand gated ion channels (ionotropic receptors) and second messenger (here G-protein) coupled (metabotropic) receptors. Ionotropic glutamate receptors can be divided into three groups: AMPA receptors, NMDA receptors, and kainate receptors.
Gamma-aminobutyric acid (GABA) is the main inhibitory neurotransmitter in the central nervous system. GABA is involved in 20 to 50 percent of brain synapses, depending on the brain area. There are three types of GABA receptors: GABAA and GABAC receptors, which are associated with chloride channels, and GABAB receptors, which are G-protein coupled (metabotropic) receptors. Binding of GABA to a GABAA receptor increases the permeability to chloride ion which leads to hyperpolarization of the neuronal membrane and to increased inhibition. A GABAA receptor contains, for example, the following binding sites: GABA, benzodiazepine and barbiturate sites.
Anesthetics bind to specific, saturable binding sites (i.e. receptors) typically on the cell membrane. Effects of anesthetics are receptor-mediated. General anesthesia may be produced by different mechanisms: anesthetics may act at different receptors or they may act at different sites of the same receptor.
At present, most of the anesthetics act primarily through GABAA-receptors. These drugs, also termed GABA agonistic agents, potentiate the actions of GABA causing hyperpolarization of the neuronal membrane. This action is common to barbiturates, propofol, etomidate, and steroid anesthetics, for example, and probably also to inhalational anesthetics.
Although most anesthesias are today conducted by GABA agonistic agents, another group of anesthetics is also used, which affects the N-methyl-D-aspartate (NMDA) receptors thereby attenuating excitatory neurotransmission. These drugs, also termed NMDA antagonists in this context, inhibit the actions of glutamate by blocking the NMDA receptors. This action is common to phencyclidine derivatives, like ketamine and S-ketamine, and to nitrous oxide and xenon, for example.
As noted above, one commonly used commercial tool for assessing the level of sedation or hypnosis is the Bispectral Index, BIS™. The BIS algorithm involves the calculation of three parameters, Beta Ratio, SynchFastSlow, and Burst Suppression Ratio, and the resulting index is a combination of the three parameters. Some of the techniques for analyzing EEG signals in an effort to determine the depth of anesthesia as well as the principles of the BIS algorithm are described in Ira J. Rampil, A Primer for EEG Signal Processing in Anesthesia, Anesthesiology, Vol. 89(4) October 1998, pp. 980-1002.
At present, the processes utilizing raw EEG signal data for monitoring a patient under sedation or anesthesia inherently assume either that during anesthesia the EMG activity is either very low and thus negligible or that the frequencies of the EMG spectrum are above the frequencies of brain activities, whereby the EMG components can be separated by methods of signal processing or spectral analysis from the EEG signal components contained in the signal data. This causes no problems in connection with the use of GABA agonistic agents, since the administration of GABA agonistic agents results in a more ordered EEG signal with spectral power concentrated onto the low frequencies. In this context, low frequencies refer to frequencies below about 20 Hz, while high frequencies refer to frequencies above about 20 Hz. A more ordered EEG signal will be the result also when NMDA antagonists are administered. However, NMDA antagonists produce both low and high frequency EEG activity, which causes BIS-based patient monitors to produce false indications and thus renders the said monitors unreliable when the said drugs are administered to the patient.
The present invention seeks to alleviate or eliminate the above-mentioned drawback and to bring about a method by means of which the BIS algorithm may be used in connection with the administration of NMDA antagonists.